Apparatus and method for detecting photon emissions from transistors

ABSTRACT

A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves spatial and/or temporal correlation of photon emissions. After correlation, the analysis may further involve obtaining a likelihood that the correlated photons were emitted by a transistor. After correlation, the analysis may also further involve assigning a weight to individual photon emissions as a function of the correlation. The weight, in some instances, reflecting a likelihood that the photons were emitted by a transistor. The analysis may further involve automatically identifying transistors in a photon emission image.

RELATED APPLICATIONS

This application is a divisional of U.S. patent application Ser. No.10/234,231 filed Sep. 3, 2002, titled “Apparatus and Method forDetecting Photon Emissions from Transistors,” which issued as U.S. Pat.No. 6,891,363 on May 10, 2005, and which is hereby incorporated byreference as though fully disclosed herein.

FIELD OF THE INVENTION

The present invention involves an apparatus and method for detectingphoton emissions from one or more transistors, and more particularlyinvolves an apparatus and method for rapidly discriminating betweenbackground photon emissions and transistor photon emissions,automatically identifying one or more transistors from photon emissiondata, and generating timing information for the identified transistors.

BACKGROUND OF THE INVENTION

The design and development of an integrated circuit (IC) oftentimesinvolves extensive testing to ensure that the IC functions correctly. Itis common for an IC to include many millions of individual CMOStransistors in various logical arrangements to perform the functions ofthe IC. The physical size of CMOS transistors is continually shrinking,and gate length as small as 0.13 microns is becoming common. Testingsuch small discrete elements of an IC is difficult or impossible toperform by physically probing the IC. Moreover, physically probing theIC can easily damage it.

Various technologies exist to test discrete transistors in an IC withoutphysically probing them. One such technology detects faint emissions oflight from functioning CMOS transistors. This technology is described inU.S. Pat. No. 5,940,545 (hereafter “the '545 patent”) entitled“Noninvasive Optical Method for Measuring Internal Switching and OtherDynamic Properties of CMOS Circuits,” which is hereby incorporated byreference in its entirety as though fully set forth herein. In someinstances, when current flows through a transistor while it isswitching, it may emit a photon. Fig. A (Background) is a diagram of aCMOS transistor 10 emitting photons 12. The '545 patent describes atechnology that can detect and record the location and time of photonemissions from a switching CMOS transistor. A commercially availableprobe system that employs aspects of the technology described in the'545 patent is the NPTest or Schlumberger IDS PICA (Picosecond ImagingCircuit Analysis) probe system.

Fig. B (Background) is a diagram illustrating an example of a photonemission image from the IDS PICA probe system. The image of photonemission data is shown overlaid on a laser scanning microscope (LSM)image of the IC for which the photon emission data was collected. Theportion of the IC shown in the LSM image is a four-line inverter block14 comprising 20 CMOS transistor pairs. A CMOS inverter comprises acomplementary pair of an NMOS (or n-channel) transistor and a PMOS (orp-channel) transistor. The dark generally vertical lines correspond withCMOS transistor pairs 16 in the inverter chain. Particularly, oneportion of the top first line of the inverter chain comprises a firstCMOS transistor pair 18 with a first p-channel region 20 arranged abovea first n-channel region 22, and one portion of the second line, belowthe first line, comprises a second CMOS transistor pair 24 with a secondn-channel region 26 arranged above a second p-channel region 28. Then-channel regions of the inverters tend to emit more photons than thep-channel regions. The bright areas 30 surrounded by dark rings areclusters of photon emissions on the image of the photon emission data. Ahigh concentration of photon emissions 32 appears adjacent the n-channelregions (22, 26) of the first and second CMOS transistor pairs (16, 24).Thus, a person viewing the photon emission data overlaid on the LSMimage might assume that the high concentration of photon emissionsadjacent the transistors were emitted by the two transistors.

With current probe systems, several factors make the identification ofphotons emitted from a transistor a timely endeavor. Some probe systemsemploying the '545 patent technology include a time and positionresolved photon counting multiplier tube (PMT) to detect single photonemissions from a transistor. With currently available PMT detectors, theprobability of detecting a near infrared photon for each switching eventis in the range of 10⁻⁷ to 10⁻¹¹ photons per switching event per μm ofgate width. The quantum efficiency of the available PMT detectors ispoor in the near infrared spectrum, but is higher in the visiblespectrum. Processing an IC to collect photon emissions involves removingsome, but not all, of the silicon 34 (see Fig. A) over the transistor.The remaining silicon allows transmission of some near infraredspectrum, but blocks the visible spectrum. Thus, the transistors in anIC must perform millions of switches before it is likely that even onephoton from each of the transistors is detected.

To exacerbate the very low probability of detecting a photon from atransistor, probe systems also detect background noise photons comingfrom the probe system itself and from other sources. Thus, transistorphoton emissions are mixed with background photon emissions. In manyinstances, probe systems require the detection of 10 million photons ormore (both from transistors and background) before a user can discernwhether photons may be attributed to transistors or background. Thedetection of 10 million or more photons may take hours or days, which insome instances may be prohibitively long.

The photon emission data collected by a probe system may be used todetermine the timing characteristics of transistors. In a normallyoperating CMOS transistor, photon emission is synchronous with currentflowing in the channel in the presence of high electric fields. Statedanother way, photons are only emitted from a CMOS transistor when it isswitching. Thus, the emission of photons from a transistor can be usedto extract timing information about the transistor.

To extract timing information for a transistor, the probe system may beused to generate a histogram of the time when photon emissions weredetected. One drawback of conventional probe systems is that they lackthe ability to process the photon emission data to automaticallyidentify photons that were emitted by transistors. Thus, to obtain ahistogram for any particular transistor, conventional probe systemsprovide a graphical user interface (GUI) for a user to manually define achannel 36 around a portion of the displayed photon emission data thathe or she believes may have been emitted by a transistor. The channel 36is shown as a rectangle in the photon emission image illustrated in Fig.B. To properly locate the channel, typically, the user will compare thephoton emission data with a schematic diagram for the IC being testedand define a channel around the photon emissions he or she suspects wereemitted by the transistor. The probe system may then generate ahistogram for the photons within the channel.

Fig. C (Background) illustrates a histogram of the timing pattern forthe photons within the channel illustrated in Fig. B. The histogramshows ten photon emission peaks 38 every 10 nanoseconds or so. Eachphoton emission peaks comprises between about 160 and 200 detectedphotons at the various time intervals. The histogram also shows numerousother photon emission detections. Because photons emitted fromtransistors occur at regular intervals and in generally the samelocation, when enough photon emissions are detected (e.g., 10 million ormore) a pattern of photon emission peaks (photon emissions that occurredat about the same time in the same area) may emerge over the backgroundnoise for a well-defined channel. Thirty-six million photons werecollected to generate the image illustrated in Fig. B and the histogramillustrated in Fig. C. As the background emissions are random, the usermay assume that the photon emissions detected at a regular interval arefrom one or more switching transistors. For testing of the IC, thetiming pattern of the photon emission peaks may be used to determine theswitching frequency of the transistor, the time when the transistorswitched, and may be compared to other transistor photon emissionhistograms.

Thus, while conventional probe systems provide extremely useful testinginformation, the time required to obtain that information can be verylong.

SUMMARY OF THE INVENTION

Aspects of the present invention dramatically reduce the time requiredto acquire a sufficient number of transistor emitted photons to extractuseful information. Implementations of the present invention can be usedto rapidly discriminate between photons emitted from transistors andbackground photon emissions. Implementations of the present inventionmay also be used to rapidly extract transistor timing information. Insome instances, data acquisition times can be reduced from several hoursor days, to only several minutes. With such reductions in acquisitiontime, emission data from an entire IC may be obtained in the time itwould take to obtain data for only a single discrete area of an IC, andprobe systems may be used to acquire data for numerous ICs in the timeit would take to acquire data for a single IC. By shortening the timefor testing and debugging of ICs, chip makers can bring new products tomarket faster than with conventional probe systems, can identify andrectify faults faster than with conventional probe systems, and canrealize numerous other advantages.

Implementations of the present invention also automatically identifytransistors from photon emission data. Upon automatic identification oftransistors, histograms for all identified transistors may beautomatically generated. This eliminates the need for a user to visuallydetermine which photon data might be from a transistor, manually selectthe photon emission data, and then generate a histogram. Moreover, thenumber of photons required to obtain highly accurate transistor timinginformation is dramatically reduced.

One aspect of the present invention involves a method for analyzingphoton emission data to discriminate between photons emitted from atransistor and photons emitted from other sources, the photon emissiondata comprising a first photon emission and at least one second photonemission, each photon emission comprising a spatial componentcorresponding with the space where each photon was detected and atemporal component corresponding with the time when each photon wasdetected.

The method comprises correlating the first photon emission with the atleast one second photon emission; and assigning a weight to the firstphoton emission as a function of the operation of correlating. Theoperation of correlating the photon emissions may further comprisecomparing the spatial component of the first photon emission with thespatial component of the at least one second photon emission todetermine if the spatial components are within a spatial range. Theoperation of correlating the photon emissions may further comprisecomparing the temporal component of the first photon emission with thetemporal component of the at least one second photon emission todetermine if the temporal components are within a temporal range.

The operation of assigning a weight to the first photon emission maycomprise assigning one weight value for each of the at least one secondphoton emissions that are spatially correlated, that are temporallycorrelated, or that are both spatially and temporally correlated.

Another aspect of the present invention involves a method for analyzingphoton emissions to discriminate between photons emitted from atransistor and photons emitted from other sources, the photon emissionscollected from a transistor using a detector having a transit timespread, the collected photon emissions comprising a spatial componentand a temporal component corresponding with the space where each photonwas detected and the time when each photon was detected. The methodcomprises receiving an indication of a group of photon emission data,the group being a subset of the collected photon emission data;processing the group of photon emission data to provide at least onetemporal subgroup of photons having similar temporal characteristics;and determining a likelihood that photons within the temporal subgroupwere emitted by a transistor.

The group of photon emission data may comprises a spatial subset of thecollected photon emission data wherein the spatial subset of thecollected photon emission data comprises each photon emission within aspatial range.

The operation of processing the group of photon emission data to provideat least one temporal subgroup of photons having similar temporalcharacteristics may further involve aggregating photon emissions indiscrete time bins, or convolving the group of photon emission data witha normalized gate function, a triangle function, a Gaussian function, orthe like. The operation of determining a likelihood that photons withinthe temporal subgroup were emitted by a transistor may further involveN-level thresholding or probability thresholding as described herein.

Another aspect of the present invention involves a method for analyzingphoton emissions collected from a transistor discriminate betweenphotons emitted from a transistor and photons emitted from othersources, the collected photon emissions comprising a spatial componentand a temporal component corresponding with the space where each photonwas detected and the time when each photon was detected. The methodcomprises spatially correlating the collected photon emissions data;temporally correlating the collected photon emission data; anddetermining a likelihood that all or a portion of the spatiallycorrelated photon emission data originated from a transistor photonemission.

The spatial correlation may involve a method for autochanneling asdiscussed with reference to FIGS. 15 and 16. The temporal correlationmay involve the operations discussed with reference to FIGS. 3A–3B, ormay involved some of the operations discussed with reference to FIGS. 9and 11. The likelihood operation may involve the operations discussedwith reference to FIGS. 3A–3B and/or the operations discussed withreference to FIGS. 5A–5C. The likelihood operations may also involveassigning a weight to the photons as a function of the spatial and ortemporal correlations.

Aspects of the present invention may also involve any of the operationsand methods described with reference to FIGS. 1–16, individually or incombination. For example, aspects of the present invention involve themethod for autochanneling described with reference to FIGS. 15 and 16.

A probe system or other system or apparatus conforming to the presentinvention may comprise program code, which when executed, performs someor all of the operations, alone or in combination, discussed in regardto the above described methods, or discussed in the detailed descriptionset forth below. In one implementation, the program code may beimplemented in non-volatile memory.

These and other features, embodiments, and implementations of thepresent invention will be described hereafter.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. A (Background) is a diagram illustrating a CMOS transmitteremitting photons;

Fig. B (Background) is a diagram of an image of photon emission datataken from a conventional probe system, the photon emission dataoverlaid on a laser scanning microscope diagram, the diagram furtherillustrating a manually defined channel around one concentration ofphoton emissions;

Fig. C (Background) is a histogram of the photon emission data withinthe channel illustrated in Fig. A, the histogram having time definedalong the x-axis and the number of photons defined along the y-axis;

FIG. 1 is a block diagram of a probe system, in accordance with oneembodiment of the present invention;

FIG. 2 is a flowchart illustrating the operations involved in a methodfor analyzing photon emission data to determine the likelihood that thephotons were emitted by a transistor, in accordance with one embodimentof the present invention;

FIG. 3A is a flowchart illustrating a method for processing photonemission data to account for jitter in the detector by aggregatingphoton emissions in time bins, in accordance with one embodiment of thepresent invention;

FIG. 3B is a flowchart illustrating a method for processing photonemission data to account for jitter in the detector by convolving thephoton emission data with a triangle function, Guasssian function, orthe like, in accordance with one embodiment of the present invention;

FIG. 3C is a flowchart illustrating a method for processing photonemission data to account for jitter in the detector by convolving thephoton emission data with a normalized gate function, in accordance withone embodiment of the present invention;

FIG. 4A is a diagram illustrating a histogram of photon emissionrecordation timing, the diagram further illustrating a plurality of timebins, in accordance with one embodiment of the present invention;

FIG. 4B is a diagram of the histogram of FIG. 4A, after the photons arecollected in the time bin and summed, in accordance with one embodimentof the present invention;

FIG. 5A is a flowchart illustrating a method for determining alikelihood that photons were emitted by a transistor, in accordance withone embodiment of the present invention;

FIG. 5B is a flowchart illustrating an alternative method fordetermining a likelihood that photons were emitted by a transistor, inaccordance with one embodiment of the present invention;

FIG. 5C is a flowchart illustrating a second alternative method fordetermining a likelihood that photons were emitted by a transistor, inaccordance with one embodiment of the present invention;

FIG. 6 is a graph illustrating the confidence or probabilityrelationship between the background photon emission of a probe systemdetector and the number of photons detected in a discrete time period,in accordance with one embodiment of the present invention;

FIG. 7A is a histogram of the number of photons collected at varioustime points for a portion of 80,000 total collected photons at asampling rate of 2.5 ps, for 0.18 um CMOS technology arranged in aninverter configuration running a test sequence at 100 MHz in a 100 nsloop;

FIG. 7B is a histogram of the photon emission data illustrated in FIG.7A processed in accordance with the method of FIG. 3A;

FIG. 7C is a histogram of the photon emission data illustrated in FIG.7A processed in accordance with the method of FIG. 3C;

FIG. 7D is a histogram of the photon emission data illustrated in FIG.7A processed in accordance with the methods of FIG. 3A and FIG. 5A;

FIG. 7E is a histogram of the photon emission data illustrated in FIG.7A processed in accordance with the methods of FIG. 3C and FIG. 5B;

FIG. 8 is a flowchart illustrating a method for automaticallyidentifying transistors from photon emission data and obtaininghistogram data for the identified transistors by correlating photonsspatially, temporally, or spatially and temporally, in accordance withone embodiment of the present invention;

FIG. 9 is a flowchart illustrating a method for assigning a weight to aphoton emission as a function of the spatial correlation with otherphotons, a function of the temporal correlation with other photons, andas a function of the spatial and temporal correlation with otherphotons, in accordance with one embodiment of the present invention;

FIG. 10A is a diagram illustrating one method for spatially correlatingphoton emissions, in accordance with one embodiment of the presentinvention;

FIG. 10B is a diagram illustrating one method for temporally correlatingphoton emissions, in accordance with one embodiment of the presentinvention;

FIG. 11 is a flowchart illustrating a method of assigning a weight to aphoton emission as a function of the spatial and temporal correlationwith other photons, in accordance with one embodiment of the presentinvention;

FIG. 12A is a diagram illustrating a method for spatially and temporallycorrelating photon emissions, in accordance with one embodiment of thepresent invention;

FIG. 12B is a diagram illustrating a second method for spatially andtemporally correlating photon emissions, in accordance with oneembodiment of the present invention;

FIG. 13 is a flowchart illustrating a method for establishing athreshold value, photons having a weight above which are attributed totransistor emissions, in accordance with one embodiment of the presentinvention;

FIG. 14A is a histogram illustrating photon emissions around onediscrete time point for conventionally obtained photon emission data;

FIG. 14B is a histogram illustrating photon emissions around onediscrete point for photon emission data correlated in accordance withthe method illustrated in FIG. 13;

FIG. 15 is a flowchart illustrating the operations involved in a methodfor auto channeling, in accordance with one embodiment of the presentinvention; and

FIG. 16 is a diagram illustrating the method for auto channelingdescribed with reference to FIG. 15.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

The present invention involves apparatuses and methods for analyzingphoton emissions from an integrated circuit (IC) to identify transistorsand extract timing information. Implementations of the present inventionprocess photon emission data to rapidly discriminate between photonsemitted by a transistor and photons attributable to backgroundemissions. Generally, various aspects of the invention involve thecorrelation, grouping, or association of photons that have the same orsimilar spatial, temporal, spatial and temporal and othercharacteristics to discriminate between photons emitted from atransistor and randomly distributed background photon emissions. Thediscrimination between transistor photon emissions and background photonemissions can be used to identify a likelihood that photons were emittedfrom a transistor, identify a single transistor, identify manytransistors in an entire IC or a portion of an IC, and extract timinginformation for the transistor or transistors.

FIG. 1 is a schematic block diagram illustrating a diagnostic andtesting optical imaging probe system 100 (hereafter “probe system”) forgathering and recording photon emissions from one or more complimentarymetal oxide semiconductor (CMOS) transistors in an IC. One such probesystem that may employ aspects of the present invention is described inU.S. Pat. No. 5,940,545 entitled “Noninvasive Optical Method forMeasuring Internal Switching and Other Dynamic Properties of CMOScircuits.” A commercially available probe system that may employ aspectsof the present invention is the NPTest or Schlumberger IDS PICA(Picosecond Imaging Circuit Analysis) probe system.

The probe system detects and records the time and position of photonsbeing emitted from switching CMOS transistors. The probe system 100includes an IC imaging station 102 that provides optical image data ofan IC under test. The probe system 100 also includes a testing platform104 that provides a testing sequence to the IC under test. Generally,the testing sequence provides a known signal pattern at the inputs ofthe IC that generates a known output pattern at the outputs of aproperly functioning IC. Due to the low probability of detecting aphoton emission, the testing sequence may be looped for a period oftime. In response to the testing sequence, the IC under test executesvarious operations, which involves the commutation or switching of CMOStransistors. Each time a CMOS transistor commutates, there is a chanceit will emit a photon. The IC imaging station 102 is configured todetect the emitted photon, and transmit the spatial location and thetime at which it received the photon to an acquisition electronicsplatform 106. A graphical user interface (GUI) 108 is accessible througha workstation connected with the probe system 100. The GUI may be usedto manipulate photon emission data collected by the IC imaging station102.

The IC imaging station 102, in one implementation, includes a detectorthat has a field of view of 4096 pixels by 4096 pixels, which may beused to obtain photon emission data for an IC area of about 160 micronsby 160 microns. Such an area may include any number of discrete CMOStransistors. The physical dimensions of CMOS transistor gate lengths areconstantly shrinking. Currently, a CMOS transistor gate length may be assmall as 0.13 microns. Hence, taking into account some space betweentransistors and the presence of ring guards, there could be thousands ofCMOS transistors in the 160 micron by 160 micron portion of the ICwithin the field of view. The field of view includes an x-axis (thehorizontal axis) and a y-axis (the vertical axis). The pixel locationthat captures an emitted photon includes an x-position and y-position.The (x, y) position where the photon is detected is transmitted to theacquisition electronics 106. In addition, the probe system 100 capturesthe time (t) at which the photon is detected, which is also transmittedto the acquisition electronics 106.

Typically, the pixel location associated with the capture of an emittedphoton is above the transistor that emitted it. The photon, however, maynot be detected directly above the portion of the transistor thatemitted the photon because the photon may be emitted at an angle. Inaddition, as discussed in more detail below, the time at which a photonis detected may be offset by the jitter of the detector. Thus, the exactspatial and temporal location that a photon is detected may be differentthan the location and time of its transmission.

FIG. 2 is a flowchart illustrating the operations involved in a methodfor analyzing photon emission data captured by the probe system todiscriminate between transistor photon emissions and background photonemissions, in accordance with one embodiment of the invention. Themethod described with reference to FIG. 2 and other related figures andFIG. 8 and other related figures may be generally considered as methodsfor event detection. The various methods described herein are discussedwith reference to implementation in the probe system of FIG. 1. Themethod illustrated in the FIG. 2 flowchart along with the other methodsdescribed herein, all in accordance with various aspects of the presentinvention, may also be implemented as executable software code. The codemay be adapted to run on the workstation connected with the probesystem, run on a server connected to a network accessible by one or moreprocessing devices, and on a standalone processing device (such as apersonal computer, workstation, or the like). The code may also berecorded on a computer readable medium, such as a floppy disk, CD-ROM,RAM, ROM, and the like.

The user of a probe system employing a method conforming to the presentinvention can rapidly discriminate between photons emitted from atransistor and photons emitted from background sources. Suchdiscrimination may be used to identify functioning transistors useful inlocating faults in a dense array of CMOS transistors located in an IC. Aprobe system employing aspects of the present invention may provide aconventional timing mode, which causes the probe system to obtain enoughphoton data to extract precise timing information for an IC under testas is known in the art, and an event detection mode configured toexecute one or more of the methods described herein, alone or incombination, which causes the probe system to obtain enough photon datato determine whether a transistor is switching. As will be discussedbelow, embodiments of the present invention are also capable ofextracting precise timing information from switching transistors in muchshorter time periods than conventional probe systems. Thus, a probesystem may employ a timing mode configured to cause the probe system toobtain photon data and process the photon data in accordance with anembodiment of the invention rather than conventional methods.

Referring again to FIG. 2, first, the probe system 100 obtains spatialand temporal characteristics for the photons detected while an IC isbeing operated (200). As discussed above, to generate photon emissions,a test sequence is run in a loop on the IC under test. The IC imagingstation 102 collects all photons from switching transistors andbackground emissions during the test sequence. The photon emission dataincludes spatial and temporal characteristics for each photon detectedby the detector while the IC is being tested. The spatial information isprovided as an x-coordinate and a y-coordinate corresponding with thepixel location that detected the photon. The temporal information isprovided as a time (t) value corresponding with the time that the photonwas detected.

As mentioned above, the field of view of the detector may include athousand or more CMOS transistors. After the photon emission data isobtained, a portion or subgroup of the photon emission data is selectedfor analysis (210). Generally, the subgrouping involves aspatially-based subgroup of all of the photons within the photonemission data. In one implementation, using the GUI 108, the userdefines a channel on the photon image data. The channel may be definedby using a mouse manipulated pointer to draw a rectangle around an areaof an image generated as a function of the photon emission data. Thechannel area is bounded by a range of x-values and a range of y-values,and all of the photons having an x-value and y-value within the channelare included in the channel. Alternatively, the subgroup or channel maybe defined through a method for identifying transistors from photonemission data discussed below with reference to FIGS. 8–16.

The methods described herein with regard to FIGS. 2–7E process asubgroup of all of the photon emission data. In contrast, the methodsdescribed below with regard to FIGS. 8–15 may process all of the photonemission data. It will be recognized that the methods described withreference to FIGS. 2–7E may be adapted to process all of the photonemission data. The photon emission data collected by the IC imagingstation may be analyzed in accordance with the methods described hereinwhile the testing sequence is running and photon emissions are beingcollected by the IC imaging station or the data may be analyzed afterthe testing loop has been completed.

After defining the group of photons to analyze (210), the systemprocesses the group of photon emissions to account for errors in theidentification of the time at which the photons were detected (220). Theprocessed data is then analyzed to determine the likelihood that thephotons in the group were emitted by a transistor (230). Referring nowto operation 220 of FIG. 2, to determine the likelihood that photons ina group were emitted by a transistor, an embodiment of the invention maytake into account the background photon emission characteristics of thedetector used to collect the photon emission data. Generally, if thebackground emission characteristics are understood, then the system maycompare the photons in a particular group with the expected backgroundphoton emission characteristics and determine whether photons in thegroup are a part of the background emission or were likely emitted bytransistors.

In some implementations of the present invention, the spatialsubgrouping of the photon emission data (operation 210) is processed toaccount for errors in the identification of the time at which a photonwas detected (220). Photon detectors, such as the PMT detector used inthe IDS PICA system, have some error in the identification of the timeat which a photon was detected, which is referred to as TTS (transmittime spread) or “jitter.” In the presence of jitter, a photon thatarrives at the detector at time t may be identified as having beenreceived at some time before t or after t. For example, if the jitter ofthe detector is 80 ps (picoseconds), then the detection time for aphoton may be anywhere within the range between t−40 ps and t+40 ps.Processing the photons to account for the jitter of the detectorinvolves a temporal subgrouping of photons to prospectively associatephotons emitted by a transistor with other photons emitted by the sametransistor, even though those photons were not recorded at or very nearthe same time.

FIGS. 3A, 3B, and 3C are flowcharts illustrating various different waysto process photon emission data (referred to as “processed photon data”)to account for the photon emission detection timing errors introduced byjitter. FIG. 3A is a flowchart illustrating a method involving thesummation of photons falling with defined blocks of time. FIG. 3Billustrates the application of various filters to process photonemission data. FIG. 3C illustrates a method involving the convolution ofphoton emission data with a normalized gate function. As will berecognized, the methods discussed with reference to FIGS. 3A–3C mayalone provide event detection, in accordance with one embodiment of theinvention. As discussed further below, further processing of the photonemission data in accordance with the methods described with reference toFIGS. 5A, 5B, and 5C may also be performed to provide event detection.

Referring first to FIG. 3A, a flowchart is shown illustrating theoperations involved in one method for processing the photon emission toaccount for the timing errors introduced by jitter. First, the systemsegments the spatially grouped photon emission data into one or morediscrete time bins (300). The system then aggregates all of the photonemissions falling within one of the time bins (310). FIG. 4A illustratesa an example of a histogram for photon emission 110 and the time oftheir detection and a graphical illustration of a set of time bins 112.Generally, a time bin defines a continuous range of time within thetotal range of time for the photon emission data being processed.Typically, a plurality of time bins are defined such that all of thetime bins account for at least the total range of time for the photonemission data being processed. For example, if a test sequence is run onan IC in a loop of 100 ns (nanoseconds), then the total range for thephoton emission data collected for the IC will be 0 to 100 ns.

In some instances, the time bins may also be defined so that theyoverlap. In a detector with a 75 ps jitter, for example, the temporalrecordation of photons emitted at the same time in the loop, mayactually be recorded within 37.5 ps on either side of the actualdetection. Thus, photons emitted from a single transistor at nearly thesame time, may be recorded within a range of 75 ps. As will berecognized fully from the discussion below, it is important to capturethe full temporal range of as many photons associated within atransistor emission as possible.

The present inventors recognized that background emissions are randomlyspread about photon emission data both spatially and temporally. Thus,it is unlikely that there will be a high concentration of photonemission detections attributable to background in a discrete locationspatially or temporally. Photons emitted from a transistor, however, areemitted from a spatially located transistor and at a temporal interval.Thus, even though photons may be deflected, emit at an angle, and emitfrom different spots on the transistor and even in the presence ofjitter, photons emitted from a transistor are likely to be fairlyclosely grouped in both space and time. If a transistor photon emissionoccurs at the boundary between two time bins, then the photon might notbe grouped with other photons emitted from the transistor. Thus, in someimplementations of the present invention that employ time bins tocompensate for error introduced by the detector, the time bins aredefined in an overlapping manner so that transistor photon emissionsmight be grouped with other related transistor photon emissions.

Referring again to FIG. 4A, in this example, sixteen 75 ps wide timebins 112 are illustrated. Each time bin has a 10 ps overlap withadjacent time bins. These time bins are arranged beginning from timezero and extending along the 100 ns loop of the histogram. The firsttime bin 114 includes 0 ps to 75 ps, the second time bin 116 includes 65ps to 140 ps, the third time bin 118 includes 130 ps to 205 ps, etc. Thearrangement of time bins shown in FIG. 4A is just one possiblearrangement. In another example, a time bin is defined as the same sizeas the jitter of the detector. In one particular implementation of thepresent invention, the time bins are defined around the sampling timepoints at the size of the jitter. If the sampling rate is 2.5 ps and thejitter is 80 ps, then the time bins would be 80 ps wide and centeredaround each sampling location. For 100 ns loop of photon emission data,the first time bin centered around the first sampling location (0 ps)would include 0 to 40 ps, the second time bin centered around the secondsampling time (2.5 ps) would include 0 to 42.5 ps, the third time bincentered around the third sampling time (5 ps) would include 0 to 45 ps,etc.

Once the photon data in the channel is grouped in the time bins(operation 300), program code running on the workstation implementingthe present invention aggregates the photons in each time bin (310). Inone example, the aggregation is the sum of the photons in each bin.Therefore, if there are four photons in a time bin, then the time bin isassociated with four photons.

The grouping and summation of photons in time bins compensates for thejitter introduced by the detector by capturing most or all of the photonemissions from a particular transistor in one time bin as opposed tobeing distributed across multiple discrete points.

FIG. 4B illustrates an example of the photon emission data associatedwith the histogram of FIG. 4A, after the photon emission data has beenbinned and summarized. Two features of the binning and summarizationoperations are illustrated in FIG. 4B. First, in the seventh bin 120, itcan be seen (FIG. 4A) that the original data had two photons 122 at onesampling time and one photon 124 at a second sampling time. In FIG. 4B,it can be seen that in the seventh time bin 120, the three photons 126are summed and centered in the time bin. Second, in the overlap 128between the eleventh 130 and twelfth 132 time bin (FIG. 4A), it can beseen that the original data has one two-photon emission peak 134. InFIG. 4B, due to the location of the two photon emission peak 134 in theoverlap region 128, it can be seen that this emission peak 136 in theeleventh time bin 130 is summed with a second one-photon emission peakand centered in the eleventh time bin. It can also be seen that thisemission peak was centered in the twelfth time bin. After the groupingand summation, the processed photon data is in condition for furtherprocessing to determine the likelihood that the photons were emitted bya transistor.

Referring to now FIG. 3B, a flowchart is shown illustrating theoperation involved in applying any one of various filters to the photonemission data to provide processed photon emission data accounting forthe jitter in the detector. As with summarizing the photon emission datawithin discrete time bins, filtering the photon emission data is a meansto account for the timing errors introduced by jitter. The filtering ofthe photon emission data comprises the convolution of the photonemission data with a specified function to obtain processed photonemission data (320). In one implementation of the present invention, thephoton emission data is convolved with a triangle function with afull-width half maximum (FWHM) of 80 ps to provide processed photonemission data. In another implementation of the present invention, thephoton emission data is convolved with a Gaussian function with a FWHMof 80 ps to provide processed photon emission data. Both filters performlow passband filtering to smooth the data. In a time region withtransistor photon emissions spread within the TTS of the detector, theconvolution will have the effect of averaging the emissions to raisethem above the level of background emissions.

Referring to FIG. 3C, a flowchart is shown illustrating the operationinvolved in convolving the photon emission data with a normalized gatefunction (330), which provides processed photon emission data accountingfor the jitter in the detector. In one example, the convolution of thephoton emission data with a normalized gate function is configured toprovide a summation of the photons in a time window of 80 ps centeredaround each sampling point, which provides results similar to thebinning and summation method discussed with reference to FIG. 3A. Thebinning and summing operation aggregates the photons in a time bin, sofour photons detected at four sampling points within the bin, may becomea single four photon count emission peak at one sampling point at thecenter of the bin. The convolution of the processed photon emission datawith a gate function, in contrast would provide four, four-photon peaksat each of the sampling points where the unprocessed one-photon emissionpeaks exist.

Event detection involves the determination of whether a photon orphotons were emitted by a transistor. Referring again to FIG. 2, afterapplication of any of the methods described with reference to FIGS.3A–3C, the processed photon emission data is further processed todetermine the likelihood that all or some of the photons within thegroup (e.g., the defined channel region) were emitted by a transistor.The determination of whether the photon emission data originated from atransistor involves a statistical analysis of the processed photonemission data that provides the likelihood or a probability that thephotons were emitted from a transistor.

FIGS. 5A–5C each illustrate a method for determining the likelihood orprobability that all or part of the photon emission data is from atransistor. FIG. 5A illustrates a method of defining an N-thresholdlevel above which the photons in the channel are likely emitted from atransistor. FIGS. 5B and 5C each illustrate a method of obtaining aprobability that the photons within the channel were emitted by atransistor. The methods in FIGS. 5A–5C, along with the methods describedearlier, provide various ways to rapidly discriminate between transistorphoton emissions and background photon emissions.

Referring now to FIG. 5A, a flowchart is shown illustrating theoperations involved in obtaining a threshold level (N) above whichphotons are likely attributable to transistor emissions (referred to as“N-level thresholding”). In one example of the present invention, thethreshold level (N) is defined as:N=Background Level+n*Noise,where n is an adjustable integer.To determine N, first, the background photon emission level (backgroundlevel) is determined (500). The background level is the sum of thephotons emitted from the detector and the photons arising from otherbackground emission sources. The photons arising from other backgroundsources tends to be very weak and in some instances it may be assumedthat the background level is only attributable to the detector. If afairly short acquisition time is implemented so that most of the photonsdetected are from background emissions, then the background level may beestimated as the mean or the median of the number of photons in eachtime bin for data processed in accordance with the binning and summingoperations described with reference to FIG. 3A, or the number of photonsat each sampling point for data processed through convolving the data asdescribed with reference to FIG. 3B or 3C.

After the background level is determined, the noise level in thebackground emission (noise) is determined (505). The noise can beevaluated by computing the standard deviation of the processed photonemission data. For the data processed in accordance with the method ofFIG. 3A, the noise is the standard deviation in the number of photons ineach time bin. For the data processed in accordance with the methods ofFIG. 3B or FIG. 3C, the noise is the standard deviation in the number ofphotons at each sampling point.

An integer “n” may be applied to the noise to adjust the threshold levelto provide a greater or lesser certainty that photons detected above thethreshold level may be attributed to transistor emissions (510). Afterthe n-value is set, the threshold level is determined (515). Thethreshold value (N) is a function of the background levels and thenoise, and defines a value above which photons are likely attributableto transistor emissions. The noise involves the standard deviation ofthe background emission levels. Thus, if an n-value of three (3) ischosen, this would represent three times the standard deviation of thenoise (three-sigma). For a threshold value of N, with a three-sigmastandard deviation, the confidence is 99.9% that photons above thethreshold N are attributable to transistor emissions.

Generally, when employing the method of FIG. 5A, if the variation inbackground photon emissions (or noise) is a small value, then thesignals attributable to photon emissions will be quickly recognized inthe processed photon emission data above the background emissions. Insuch a case, a smaller n-value may be used, which will reduce thethreshold level. With a lower threshold level, it will take less time toacquire sufficient transistor photon emissions to exceed the thresholdand have a high confidence level or likelihood that the photons wereemitted by a transistor. On the other hand, if the variation inbackground emissions is high, then the signals attributable to photonemissions will not be recognized as quickly in the processed photon dataabove the background emissions. In such a case, a larger n-value mightbe used to obtain the same confidence that the photon emissions areattributable to a transistor. Thus, greater background emission noisecan result in longer acquisition times to reach a high confidence level(e.g., 99.9%).

Referring now to FIG. 5B, a flowchart is shown illustrating theoperations involved in determining a probability or likelihood that allor some photons in the processed photon data were emitted by atransistor. This probability determination involves Poisson statistics.For any set of processed photon emission data, it is possible todetermine the mean background photon emissions for the processed photondata and compute the probability of having N photons from backgroundemissions. If it is assumed that the distribution of background photonemissions follows Poisson statistics, then the probability of having Nphotons attributable to background emissions (of the detector TTS wide)is given by:

${\Pr( N_{Background} )} = \frac{{\mathbb{e}}^{- \mu} \cdot \mu^{N}}{N!}$

μ=mean of background emissions.

N=total number of detected photons.

To implement the above probability determination (PR(N_(Background))),the total number of photons detected (N) while the IC was being testedis determined (520). In addition, the mean (μ) or the median of thebackground photon emissions is determined (525). For the binnedprocessed data, the mean or the median of the background photonemissions is the mean or median of the number of photons in each timebin. For the convolved processed data, the mean or the median is takenfor the number of photons at each sampling point. With the total numberof photons and the mean of the background photon emissions, theprobability of having the mean number of photons in the time bin due tobackground emissions may be determined in accordance with the aboveequation for Pr(N_(Background)) (530).

The probability of having N photons from transistor emissions (535) isgiven by:N _(Transistor)=1−Pr(N _(Background))Thus, for example, if there are four photons in a time bin and theprobability of those photons being attributable to only backgroundemissions is 20%, then the probability of those photons beingattributable all or in part to transistor emissions is 80%.

Once the probability is determined, the probability of the photonshaving been emitted from a transistor may be displayed (540). Theprobability may be displayed collectively for the photons aggregated ina time bin, or may be displayed individually for the photon processed inaccordance with the methods of FIG. 3B or FIG. 3C. Generally, a higherprobability that the photons were emitted by a transistor translatesinto a higher confidence that the photon emissions are attributable to atransistor and not background emission.

In addition, a cutoff may be applied to the probability to only displayphotons that meet or exceed the cutoff (545). Generally, the cutoff isdefined such that the probability of having photons below the cutofflevel that are due to background emissions is so low that it is likelythat some or all of the photons are attributable to transistoremissions. The cutoff level is adjustable, in one example a photonemission is considered likely if:Pr(N _(Background))<0.1%, or Pr(N _(Transistor))=99.9%Thus, the cutoff is set at 99.9%, so only photons with a 99.9%probability of having been emitted by a transistor are kept anddisplayed either in a photon index or histogram, or both. For example,if there are eight photons in the time bin and the probability of thosephotons being attributable to only background emissions is less than0.1%, then the binned photon value will exceed the cutoff and bedisplayed.

Referring now to FIG. 5C, a third method for determining the probabilityor likelihood that photons were emitted by a transistor is illustrated.For event detection as opposed to conventional precise timing detection,it is often adequate to identify that an event has occurred with someprobability. In one implementation of the present invention as discussedabove, the photon emission data may be processed with the bin widthdefined as the jitter or the TTS, Δt_(TTS), of the detector. With a binwidth equal to the jitter width, the average number of backgroundemissions per bin is equal to:

${\Delta\; N_{dk}} = \frac{R_{dk} \cdot T_{acq}}{{T_{loop}/\Delta}\; t_{TTS}}$

T_(acq)=acquisition time

T_(loop)=loop length

Δt_(TTS)=TTS of detector (120 ps for the Mepsicron II)

Δt_(res)=time resolution of the measurement

S_(ph)=detected signal photons/switch/um (depends on device technology)

w_(gate)=gate width (total gate width if device has multiple stripes)

R_(dk)=dark counts/s (in the signal channel) (“dark count” refers tophotons emitted by the detector)

SNR=signal-to-noise ratio

$T_{acq} = {T_{loop} \cdot ( \frac{\Delta\; t_{TTS}}{\Delta\; t_{res}} )^{2} \cdot \frac{{w_{gate}S_{ph}} + {\Delta\; t_{TTS}R_{dk}}}{( {w_{gate}S_{ph}} )^{2}}}$To determine εN_(dk), the background photon emission rate, N_(dk)(operation 550), the photon acquisition time, T_(acq) (operation 555),the loop time, T_(loop) (operation 560), and the jitter of the detector,Δ_(TTS) (operation 565) are each obtained. With these values, the systemcan determine the average background photon emission for the processedphoton data (570).

The background photon emissions are randomly spaced and followPoissonian statistics. The probability of finding N photons in a bin(575) is thus equal to:

${P_{\Delta\; N_{dk}}(N)} = \frac{{\mathbb{e}}^{{- \Delta}\; N_{dk}}\Delta\; N_{dk}^{N}}{N!}$If a threshold is set at N photons, then the probability of finding N ormore photons per bin is:

${P_{\Delta\; N_{dk}}^{geq}(N)} = {{\sum\limits_{x = 0}^{N}{P_{\Delta\; N_{dk}}(x)}} = {\sum\limits_{x = N}^{\infty}\frac{{\mathbb{e}}^{{- \Delta}\; N_{dk}}\Delta\; N_{dk}^{x}}{x!}}}$The average number of bins with more than N photons (580) is then equalto:

$\begin{matrix}{{n(N)} = {{\frac{T_{loop}}{\Delta\; t_{TTS}}{P_{\Delta\; N_{dk}}^{geq}(N)}} = {\frac{T_{loop}}{\Delta\; t_{TTS}}{\sum\limits_{x = N}^{\infty}\frac{{\mathbb{e}}^{{- \Delta}\; N_{dk}}\Delta\; N_{dk}^{x}}{x!}}}}} & \;\end{matrix}$In order for the bin with N photons to be caused by signal photons, thelikelihood that the N photons are result of background emissions shouldbe set to a small value. In one implementation, n(N)<<1. n(N) is theprobability that the bin with N photons are attributable to backgroundemissions, so 1−n(N) is the probability that the N photon bin isattributable to transistor emissions.

FIG. 6 is a graph illustrating 1−n(N) as a function of the backgroundemission rate of the detector. The graph in FIG. 6 shows that as thebackground emission rate increases, more photon emissions must becollected to achieve a given likelihood that the photons were emitted bya transistor.

FIG. 7A is a histogram of a full-sampling of data taken at a samplingrate of 2.5 ps for a 0.18 um CMOS inverter chain, running a testsequence at 100 Mhz. The y-axis is photon detections, and the x-axis istime in nanoseconds (ns). The sequence runs for 100 ns (1×10⁻⁷ second)before repeating in a loop. The x-axis is thus 100 ns. With a frequencyof 100 MHz, the clock cycle is 10 ns (0.1×10⁻⁷ second). Thus, aswitching event can be expected every 10 ns. The sampling rate is 2.5ps; thus, there are 0.1*10−7 (clock cycle)/2.5*10−12(samplingrate)=40,000 sampling points between each cycle. The 80,000 photonscollected for the full-sample data were obtained in 2 minutes 45seconds.

FIG. 7B illustrates a histogram of the full-sample data illustrated inFIG. 7A after the binning and summing operations of FIG. 3A areperformed. The data was processed with each time bin being 80 ps wideand having a 10 ps overlap with the adjacent time bin. Referring to FIG.7A having the full sample data shows an emission peak at 20 ns (twophotons), 40 ns (three photons), 50 ns (two photons), 70 ns (twophotons), 80 ns (three photons), and 90 ns (two photons). Emissionpeaks, however, are not shown at 0 ns, 10 ns, 30 ns, and 60 ns. Incomparison to the full-sample data of FIG. 7A, the binned and summeddata shown in FIG. 7B illustrates more pronounced emission peaks at eachof the cycle points (i.e., 10 ns, 20 ns, etc.). A properly functioningswitching transistor emits photons at the cycle points. For example, atthe 10 ns time point, no emission peak is shown in the full-sample datawhereas an emission peak of six photons is shown in the binned andsummed data. In another example, at the 70 ns time point of thefull-sample data, a two photon emission peak is shown, whereas a tenphoton emission peak is shown at the 70 ns time period in FIG. 7B.

The emergence of the emission peaks in the binned and summed data ofFIG. 7B is a result of the high concentration of photons around the timeperiod when a transistor switches. For example, due to jitter, around orat the 10 ns time period, there is likely to be several emissions veryclosely spaced but not exactly at the same sampling point. When thesepoints are summed in a bin around the 10 ns period, the photon emissionpeak emerges as shown in the histogram for the binned and summed data.The photon emission peak includes six photons, thus there were sixphotons closely spaced together in the 80 ps time bin centered at the 10ns sampling point.

FIG. 7C illustrates a histogram for the full-sample emission dataconvolved with a normalized gate function. The results of theconvolution with the normalized gate function are similar to the resultsfor the binned and summed data. Notably, the emission peaks for both thebinned and summed data and the combined data are more pronounced thanthe full-sample data. Stronger emission peaks than even the summed andbinned data, however, can be seen at the 0 ns (ten photons), 20 ns(seven photons), 40 ns (thirteen photons), 50 ns (fourteen photons), 60ns (ten photons), 70 ns (fifteen photons), 80 ns (fourteen photons), and90 ns (nine photons) sampling points. From FIGS. 7B and 7C it can beseen that the binning and summing operations and the convolution with anormalized gate function provide a stronger indication of transistoremissions than does the full-sample data shown in FIG. 7A. Thus, boththe binning and summing operation or the convolution with a normalizedgate function to obtain processed photon data might be used alone forevent detection, in accordance with the present invention. Both of thesemethods, however, may lead to the detection of false events unless asufficient number of photons are collected or a cutoff level isappropriately determined. For example, in FIG. 7B, there is a peakbetween the 10 ns sampling point and the 20 ns sampling point andbetween the 20 ns sampling point and 30 ns sampling point. If a cutofflevel of one photon were used, then these two events may be falselydetected as transistor emissions. In FIG. 7C, a false event between the10 ns and 20 ns sampling point and the 20 ns and 30 ns sampling pointcan also be seen if a cutoff of one photon were used.

FIG. 7D illustrates a histogram of the full-sample data of FIG. 7Aprocessed using the N-level thresholding method described with referenceto FIG. 5A. In this histogram, peaks at each of the 10 ns cycle pointsare clearly shown. An N-threshold level is illustrated as the dashedline near the bottom of the histogram. The N-threshold level wasdetermined with an n-value of six thus providing a 99.999% probabilityor confidence level that photons above the dashed line are attributableto transistor emissions. FIG. 7E is a histogram illustrating thefull-sample data processed using probability level thresholding. In thisexample, a photon threshold level of three was set above which any peakemerging could be attributable to transistor emissions with a 99.999%probability. Thus, for any emission peak rising above the N-thresholdlevel or the probability level there is a 99.999% likelihood that thesepeaks are due to transistor emissions. As there are no peaks risingabove the threshold that are not at the 10 ns time cycles, it can beseen that no background emissions were falsely detected as transistoremissions. Thus, N-level thresholding and probability thresholding(FIGS. 7D and 7E) in conjunction with processing the photon emissiondata provides a more accurate indication of transistor emissions in ashorter time period than the processed photon data alone (FIGS. 7B, 7C).

The various embodiments of the present invention discussed above withregard to FIGS. 1–7E, in some instances, involve the processing of adiscrete set or group of the photon emission data to identify atransistor or transistors and to extract timing information. Thefollowing embodiments of the present invention discussed with referenceto FIGS. 8–16, in some instances, involve the processing of the entireset of photon emission data to identify a transistor or transistors andto extract timing information. It will be recognized that some aspects,operations, and features may be useful in various combinations of theembodiments.

The embodiments of the present invention discussed hereafter involvediscriminating between photon emitted by transistors and photons emittedby other background sources by processing of the photon emission data tocorrelate photons spatially and temporally. The correlation may providefor rapid identification of photons emitted from switching transistorsand for rapid extraction of accurate timing information for theswitching transistors. The correlation may also provide for autochanneling of transistors in the photon image data. The correlation maybe applied to photon emission data from a single switching transistor orfor photon emission data from numerous switching transistors.

As discussed above, a conventional probe system requires the user tomanually identify the photon emission data in the field of view forwhich to obtain timing information. This is performed by using GUI ofthe workstation to define a channel around the photons to analyze.Besides having to manually identify the photons to analyze, suchconventional systems oftentimes require a substantial amount of time toobtain sufficient photon emission data so that the photons emitted fromtransistors are identifiable over the background emissions and so thatuseful timing information may be extracted. Implementations of thepresent invention rapidly and automatically identify transistors in thefield of view, and rapidly extract transistor photon emission data fromthe identified transistor useful in timing analysis.

FIG. 8 is a flowchart illustrating the overall operations involved inrapidly and automatically discriminating between photons emitted fromtransistors and photons emitted from other background sources, andextracting useful timing information for the transistor or transistorsassociated with the photons emitted from transmissions. First, the ICimaging station 102 obtains photon emissions from an operating IC andthe acquisition electronics 106 records the photon emission data in adatabase or other memory structure (800). Each recorded photon emissionincludes, in one example, both a spatial (x, y) and temporal (t)component.

In other implementations of the present invention, photon emission dataobtained with a superconducting single photon detector may be analyzed.Such a detector is described in copending and commonly owned applicationSer. No. 09/628,116 filed on Jul. 28, 2000, titled “Superconductingsingle photon detector,” which is hereby incorporated by reference asthough fully set forth herein. In some instances, data collected with asingle photon detector will only have a time component. These detectorshave very little background emissions; thus, they are able to rapidlyextract precise photon emission timing information. The single photondetector may be arranged to obtain photon emission data at the same timeas the detector of the probe system 100. Embodiments conforming to thepresent invention may be used to correlate data from the single photondetector with photon emission data from the detector of the probe system100.

After photon emissions are obtained for the IC under test, eachtransistor in the field of view is identified (810). The transistors areidentified by correlating the photons recorded in the field of view withother photons in the field of view. The correlation may use only thespatial characteristics of the photons, only the temporalcharacteristics of the photons, or both. Probe systems detect bothrandom background photon emissions and photon emissions from switchingtransistors. Implementations of the present invention automaticallydiscriminate between background emissions and transistor emissions toidentify transistors in the field of view. Generally, photon emissionsthat are closely correlated in space may be associated with a transistorrather than background. Moreover, photon emissions that are closelycorrelated in time may also be associated with a transistor ratherbackground. Aspects of the present invention utilize the correlation ofphotons in space, in time, or both in space and time, to identifyphotons that are likely emitted from a transistor rather than backgroundsources, and thereby identify transistors in the field of view.

The correlated photons may then be used to generate accurate timinghistograms for the detected transistors (820). The correlation of thephoton data tends to provide dense clusters of photons at thecommutation points of the transistor. By comparing the timing intervalsbetween the clusters, the switching time of the transistors may beidentified.

FIG. 9 is a flowchart illustrating the operations involved in a methodfor correlating photons and automatically identifying transistors fromthe correlated photon data in accordance with one embodiment of theinvention. In one implementation of the invention, each photon isanalyzed to determine if it correlates with other recorded photonseither spatially, temporally, or both. The number of spatially and/ortemporally correlated photons is used to generate a weighting that isapplied to the selected photon.

As with other methods discussed herein, the system obtains photonemission data for an IC within the field of view of the detector. Toobtain photon emission data from the IC that may be used to diagnosefaults in the IC, a test sequence that causes the transistors to switchstates is run on the IC at a known frequency. As discussed above,switching states may cause CMOS transistors to emit a photon. Theprobability of a transistor emitting a photon during a single switchingevent, however, is extremely small. In some instances, the probabilityof detecting a near infrared photon for each switching event rangesbetween 10⁻⁷ to 10⁻¹¹ photons per switching event per μm of gate width.Thus, the test sequence may be repeated in a loop so that some photonemissions from each of the transistors in the field of view will likelybe detected.

While the test sequence is being run, the probe system records thespatial and temporal characteristic of each detected photon. In onespecific implementation, each recorded photon emission includes anassociated x-component, y-component, and time component. The field ofview for the Schlumberger IDS PICA probe system includes an x-region orhorizontal region that is 4096 pixels wide and a y-region or verticalregion that is 4096 pixels high. The x-component of the recorded photonemission data corresponds with the position or pixel location along thex-axis where the photon is detected. The y-component of the recordedphoton emission data corresponds with the position or pixel locationalong the y-axis where the photon is detected. The time component of therecorded photon emission data corresponds with the time during aparticular loop when the photon is emitted or recorded.

After the test sequence is complete, each of the recorded photons arecorrelated with other recorded photons. The operations illustrated inFIG. 9, relate to correlating one photon with the other recordedphotons. The operations may be repeated as many times as necessary toprocess all of the recorded photons in the collected photon emissiondata. In other implementations, it is possible to identify a subset ofall of the recorded photons, and only correlate those photons with otherphoton in the same subset. Such a subset may also be identified as aspatial subset, a temporal subset, or both. Depending on theconfiguration of the system, operations may be performed while the testsequence is running on the IC, immediately after the test sequence iscomplete, or at any time after the test sequence is run and the photonemission data has been recorded.

Referring again to FIG. 9, first, the system or the user selects oneparticular photon to analyze (900). Typically, the system runs thecorrelation on all photons in the photon emission data. Next, the systemanalyzes the selected photon to determine if any of the other photons inthe field of view spatially correlate with the selected photon (910). Inone implementation of the present invention, to spatially correlate theselected photon with other photons in the photon emission data, thesystem determines the number of photons within a set spatial areasurrounding the selected photon.

FIG. 10A is a diagram illustrating one way that photons maybe spatiallycorrelated. In this example, to determine if any photons spatiallycorrelate with the selected photon 140, the system determines the numberof photons in an area 20 pixels by 20 pixels centered on the selectedphoton. Thus, in this example, the three photons 142 in the area 10pixels above and below the selected photon and 10 pixels to either sideof the selected photon will be counted and considered to spatiallycorrelate with the selected pixel. The two photons 144 outside this areawill not correlate with the selected photon.

The spatial correlation area used to determine which photons arecorrelated with the selected photon may be adjusted according to the anynumber of factors. Generally, one objective is to define the spatialcorrelation area so that it likely encompasses photos emitted from theselected transistor, but does not likely encompass photos emitted fromother nearby transistors. Any number of factors may effect the spatiallocation at which photons emitted from the selected photon are detected,such as, the size of the transistor, the size of the channel region inthe transistor, the current flow through the channel region, theswitching voltage of the transistor, the spatial separation oftransistors in the IC, the noise in the system, or end the angle atwhich photons are emitted from the transistor.

In one implementation of the present invention, the number of photonslocated in the spatial correlation area is used to generate a weight forthe selected photon. For each photon in the spatial correlation area,the selected photon is associated with one weight point. Thus, with fourtotal photons in the spatial correlation area, the spatial weight forthe selected photon is four. In this implementation, only the number ofphotons in the spatial correlation area is used to generate the weight.The temporal relationship with other photons is not used to determinethe weight. Generally, background photons are detected in a spatiallyrandom pattern. Thus, the present inventors recognized that if there isa high concentration of photons in a particular spatial area, then thosephotons may be associated with transistor emission rather thanbackground emissions.

In some instances, background photon emissions may nonetheless appear inspatial relation to each other or to transistor photon emissions andthus give the impression of transistor emissions. Accordingly, inanother implementation of the present invention, the system furtherdetermines if any of the photons in the photon emission data temporallycorrelate with the selected photon (920). To temporally correlatephotons, the system determines the number of photons in a set temporalarea surrounding the selected photon. The temporal correlation area orrange may be defined in any number of ways. For example, the temporalarea may be set at 50 ps. In this example, any photon that is detectedeither 25 ps before or 25 ps after the selected photon, is correlatedwith the selected photon. In another example, the jitter of the detectormay be used to define the temporal area in which to correlate photons.Thus, for example, if the jitter is 80 ps, then the temporal area bywhich to correlate photons is set at 80 ps.

FIG. 10B is a diagram illustrating one way that photons are temporallycorrelated. The diagram at FIG. 10B corresponds with the diagram at FIG.10A. In this example, there are two additional photons 146 in the 50 psrange around the selected photon 140. There are two photons 148 outsidethe 50 ps range. Recall, in FIG. 10A it can be seen that there are threephotons in the spatial range around the selected photon.

As with the spatial correlation, each photon that is temporallycorrelated with the selected photon is used to generate a temporalweight for the selected photon. Thus, if there are three total photonsin the set temporal area, then the temporal weight for the selectedphoton is three. In one implementation of the present invention, onlythe number of photons in the temporal correlation area is used togenerate the weight. The spatial relationship is not used.

After generation of the spatial and temporal weights, an overall weightmay be assigned to the selected photon that is a function of the spatialand temporal weights (930). The weight, whether described with referenceto operation 930 or operation 1120, provides an indication of thelikelihood that the photon was emitted from a transistor. In oneexample, the overall weight is the sum of the spatial weight and thetemporal weight. Thus, if the spatial weight is four (4) and thetemporal weight is three (3), then the overall weight is seven (7). Inthe above described method of correlating photons as a function of thespatial and temporal characteristics, the spatial correlation and thetemporal correlation are completed independently, and the overall weightis the summation of the two independent weight determinations.

In another implementation of the present invention, the overall weightmay be assigned as the lesser or greater of the spatial and temporalweight. Thus, the overall weight would be three (3) or four (4),respectively. It is possible that some photons will be only correlatedin space or in time, but not in both.

In an alternative implementation of the present invention, thecorrelation of the spatial and temporal characteristics of neighboringphotons is performed so that photons must be within a certain spatialrange and a certain temporal range. As with the method of FIG. 9, thecorrelation discriminates between photons emitted from transistors andbackground sources. FIG. 11 illustrates a flowchart of the operationinvolved in one method for performing temporal and spatial correlationof photons within photon emission data, in accordance with the presentinvention. First, a particular photon from all of the photons within thephoton emission data is selected for spatial and temporal correlation(1100). As will be recognized, the operations involved in correlating aphoton with other photons may be repeated until all of the photons inthe photon emission data are processed.

The selected photon is then compared to other photons within the photonemission data to determine how many photons are within a set distanceand time (1110). The size of the correlation distance and time may beset to any number of different ranges. In one example, the distance orspatial correlation may be set at 20 pixels and the temporal correlationset at 80 ps. It is also possible to define the correlation regionaround the selected photon in many different ways. For example, FIG. 12Aillustrates spatial correlation and temporal correlation centered aroundthe selected photon 150. The spatial correlation defines a 20 pixel(x-component) by 20 pixel (y-component) square centered on the selectedphoton. Thus, any photons within 10 pixels above, below, or to eitherside of the selected pixel will be considered spatial correlated. Thetemporal correlation is defined as a range of time between 40 ps beforethe detection of the selected photon and 40 ps after the detection ofthe selected photon. Thus, the spatial and temporal range define a cubecentered on the selected photon.

Alternatively, as shown in FIG. 12B, the spatial correlation may definea 20 pixel by 20 pixel square, with the selected pixel in the upper leftcorner of the square. Thus, any photons 20 pixels to the right and 20pixels below the selected photon will be considered spatiallycorrelated. Likewise, the temporal correlation may define a 80 ps rangeonly ahead of the time at which the selected photon was detected. Thus,the spatial and temporal range define a cube within the selected photonin a corner. Alternatively, the correlation might be arranged in otherways, such as detecting photons up and to the left of selected photonand only behind the selected photon (not shown).

Only the photons within both the spatial and temporal ranges of theselected photon are used to weight the selected photon (1120). Thus, forexample, referring to FIG. 12A, there are three photons 152 that arewithin the cube defined by the x, y, and t axes (i.e., the spatial andtemporal range). There is a fourth photon 154 that is within the spatialrange, but is not within the temporal range. There are two photons (154,186) completely outside the cube. Thus, the weight for the selectedphoton is three. Referring to FIG. 12B, there are two photons 158 withinthe cube defined by the x, y, and t axes. There is a third photon 160that is within the temporal range, but is not within the spatial range.There are two photons 162 that are not within the spatial or temporalcorrelation area. Thus, the weight for the selected photon 180 is two.

Referring again to FIGS. 9 and 11, after each of the photons in thefield of view are analyzed to determine if they correlate with otherphotons in the field of view spatially, temporally, or both, and anappropriate weight is assigned to the photons, the transistors in thefield of view may be identified (operations 940 and 1130, respectively).The assigned weight generally provides an indication of the probabilitythat the photon was emitted by a transistor. Thus, the weight may beused to discriminate between photons emitted by a transistor andbackground photons. In addition, a threshold or cutoff valve may beapplied to only display photons with a certain weight.

In one implementation, all of the photons from the photon emission dataare displayed in colors according to weight. A color may be assigned toeach weight, or colors may be assigned to various ranges of weight. In asimple example, all photons with a weight of four will be red and allphotons with a weight of only one will be white. The red photons willlikely be from a transistor and will stand out from the white photons.The contrast between the colors will provide the user with an indicationof where the functioning switching transistors in the photon emissiondata are located. Besides displaying the photons accorded to weight, theweighted photon emission data may be processed in other ways.

FIG. 13 is a flowchart illustrating one example of the operations forestablishing and applying a threshold to a set of photon emission datato further identify transistors. Generally, photons with a weight,either spatial, temporal, or some combination of spatial and temporal,meeting or exceeding a threshold value are associated with a transistor,and all photons having a weight less than the threshold value areassociated with background noise. The threshold value may be based onanecdotal information, statistical analysis of the photon emissioncharacteristics of the transistors being analyzed, and by other means.Referring to FIG. 13, in one example, the system determines the highestweight for any of the photons in the field of view (1300). The thresholdis set as a percentage of the highest weight (1310). For example, thethreshold value may be set at 20% of the highest weight value. Thus, ifthe highest weight for any photon in the field of view is 15, then thethreshold value is set at three.

After the threshold value is determined and applied against the photons,the system associates each photon having a weight of equal to or greaterthan the threshold value with a transistor (1320). Thus, in the aboveexample, each photon having a weight of three or more is associated witha transistor. To illustrate transistors in the field of view, allphotons associated with a transistor may be displayed in the spatiallocation, i.e., at the same x and y pixel location, that they weredetected, and each photon having a weight of two or less is notdisplayed. Alternatively, event photons may be displayed with one color,and background photons displayed with a second color. In a histogram,only photons exceeding the threshold are displayed.

Correlated photon data, provided in accordance with the presentinvention, may also provide very accurate timing information for thetransistors associated with the photon emission data. Moreover, suchaccurate timing data may be provided in a period of time considerablyless than the same accuracy of timing data that is provided fromconventional probe systems.

FIG. 14A is an illustration of photon emission data provided by aconventional probe system. The photon emission data is for onecommutation point of a switching transistor. Due to the jitter of thedetector, photon emissions 164 are detected in a range of the jitteraround the commutation point 166. To extract timing information from thehistogram, a centroid 168 is determined for all of the photon emissionswithin the range of the jitter for the detector. To obtain enough photonemissions to obtain an accurate centroid the system must be run longenough in order to detect numerous photon transistor emissions.

In comparison, FIG. 14B illustrates a histogram for correlated photonemission data. Due to the weighting of photon emissions in both spaceand time, a well defined photon emission peak 170 emerges with very fewphoton detections. In this example, three photons 172 are correlated inboth space and time at the commutation point for the transistor. Becausethe three photons are correlated in both space and time, each willreceive a weight of three. Without correlation in both space and time,each would have a value of only one and thus would not arise above thebackground photon emission level. Being weighted, however, each value isthree times the background emission level. As with the raw histogramdata, the centroid of the three weighted photon emissions may bedetermined. This centroid may be compared with the centroid of otheremission peaks to extract the precise timing information for thetransistor associated with the histogram. In this example, only threephoton emissions for the transistor are required in order to extractprecise timing information. In the example illustrated in FIG. 14A,fifty-one photon emissions are detected before accurate timinginformation can be extracted. Depending on many factors, the number ofphoton emissions required for conventional systems to extract timinginformation may vary. Nonetheless, the number of photon emissions tendsto be dramatically more than is required with the correlation methodsdescribed herein.

The present invention also involves a method for automaticallychanneling photon emission data. Auto channeling analyzes the correlatedphoton emission data to identify spatially and temporally relatedclusters of photons. If the cluster of photons is large enough andclosely related in space and time, then the photons are considered tohave been emitted from a transistor. On the photon emission image, arectangle is drawn around the cluster of photon emissions. Inconventional probe systems, a user manipulating a GUI may define arectangle, i.e., channel, around a suspected group of photons that wereemitted from a transistor. Before such a group of photons may berecognized, a tremendous number of photons have to be collected in orderfor a large enough concentration of photons to emerge from thebackground emissions. Using the correlation methods described herein,photons closely correlated in space and time have much higher weightsthan photons that are not correlated in space and time. As discussedabove, photons exceeding a certain weight are considered to have beenemitted by a transistor. Auto channeling sorts through all of the photonemission data to identify clusters of highly weighted photons. Theseclusters of high weight photons are considered to have been emitted froma transistor.

FIG. 15 is a flowchart illustrating the operations involved in autochanneling, in accordance with one embodiment of the present invention.Generally, auto channeling involves a structured search of the photonemission data along the x, y, and t axes to identify clusters of highweight photons. In one implementation, the search begins at t=0, x=0,and y=0 (1600). FIG. 16 is a diagram illustrating a search of the photonemission data to identify clusters of photons having a weight exceedingthe threshold value above which photon emissions are attributable totransistor emissions.

The search begins by incrementing x until a photon with a weightexceeding the threshold value is detected (1605). Generally, the x-valueis incremented until it reaches 4095 which is the field of view pixelsize (1610). At x=4096, x is set to 0 and y is incremented (1615). Thesearch precedes in a serpentine manner until a y-value of 4096 isreached (1620). When y=4096, the time value is incremented by the jitteror other time increment (1625). If the jitter is 80 ps then the timevalue is incremented by 80 ps. After the time is incremented, x and yare reset to 0 and the search continues with incrementing x-values andincrementing y-values until the entire correlated photon emission dataset is autochanneled (1630).

During the search, when a weight value equal to the threshold isdetected (1635), a cube around the photon is defined (1640). The cubeincludes a spatial range (x-range, y-range) and a temporal range. In oneexample, the x-range and y-range are each 20 pixels and the time rangeis 80 ps. The first corner of the cube is defined asx_(photon-10 pixels), y_(photon-40 pixels), t_(photon-40 ps). Thus, thephoton occupies the center of the cube and the x, y and t axes extend inall direction from the photon.

Once the cube is defined, all photons within the cube meeting orexceeding the threshold value are identified (1645). After all thephotons are identified, then the number of photons identified iscompared with a second threshold value (1600). If the number ofidentified photons exceeds the threshold value, then this cluster ofphotons is considered to be a transistor. To automatically display achannel around the cluster of photons in the cube, a rectangle is drawnaround the x-range and y-range of photons that were identified (1655).

As discussed above, photons meeting or exceeding the weight value areconsidered to have likely been emitted from a transistor. A photon ofsuch weight by itself, or in the presence of a very few other photonswith such weight, may or may not have been emitted from a transistor asthese photons may be attributable to background emissions.

In addition to automatically identifying transistors from photonemission data, spatially and temporally correlated photon emission datamay also be used to extract accurate timing data for each of theidentified transistors in much less time than is typical forconventional probe systems. Photons emitted from a transistor tend to beclustered in both space and time. Thus, in most situations, transistorphoton emissions from the same transistor will have the same or nearlythe same weight after the spatial and temporal correlation methodologiesdiscussed above are applied.

While various embodiments of the invention have been particularly shownand described, it will be understood by those skilled in the art thatvarious other changes in the form and details may be made withoutdeparting from the spirit and scope of the invention, which is definedby the following claims.

1. A method for analyzing photon emissions to discriminate betweenphotons emitted from a transistor and noise, the photon emissionscollected from a transistor using a detector having a transit timespread, the collected photon emissions comprising a spatial componentand a temporal component corresponding with the space where each photonwas detected and the time when each photon was detected, the methodcomprising: receiving an indication of a group of photon emission data,the group being a subset of the collected photon emission data;processing the group of photon emission data to provide at least onetemporal subgroup of photons having similar temporal characteristics;and determining a likelihood that photons within the temporal subgroupwere emitted by a transistor rather than noise by temporally correlatingat least one first photon from the temporal subgroup with at least onesecond photon from the temporal subgroup.
 2. The method of claim 1wherein the group of photon emission data comprises a spatial subset ofthe collected photon emission data.
 3. The method of claim 2 wherein thespatial subset of the collected photon emission data comprises eachphoton emission within a spatial range.
 4. The method of claim 3 whereinthe spatial component of the photon emission data comprises an x-valueand a y-value, and wherein the spatial range comprises an x-range and ay-range.
 5. The method of claim 1 wherein the operation of processingfurther comprises defining a plurality of time bins, each time bindefining a temporal range.
 6. The method of claim 5 further comprisingaggregating all photons within the temporal range.
 7. The method ofclaim 5 wherein the temporal range is set as the transit time spread. 8.The method of claim 1 wherein the operation of processing furthercomprises, for each photon within the group, summing the number ofphotons within a set temporal range.
 9. The method of claim 8 whereinthe temporal range is set as the transit time spread.
 10. The method ofclaim 1 wherein the operation of processing further comprises convolvingthe photon emission data with a triangle function, Gaussian function orother function that performs low passband filtering.
 11. The method ofclaim 10 wherein a full-width half maximum of the triangle function isset as the transit time spread.
 12. The method of claim 10 wherein afull-width half maximum of the Gaussian function is set as the transittime spread.
 13. The method of claim 10 wherein the operation ofdetermining further comprises: determining a background photon emissionlevel; determining a noise level of background photon emissions;receiving an indication to adjust a threshold level to provide greateror less certainty that photons detected above the threshold level may beattributed to transistor emissions; and obtaining the threshold level(N) of number of photons attributed to background and noise.
 14. Themethod of claim 13 wherein the noise level is set at the standarddeviation in the number of photons at each sampling point.
 15. Themethod of claim 10 wherein the operation of processing furthercomprises: determining a total number of photons detected in the photonemission data; determining a mean of background photon emissions;determining a probability of having the mean number of photons due tobackground emissions; and determining a probability of having a meannumber of photons due to transistor emission events.
 16. The method ofclaim 10 wherein the operation of processing further comprises:obtaining a dark count per second for the detector; obtaining time ofphoton acquisition; obtaining loop length; obtaining transit time spread(jitter) of the detector; determining average number of backgroundphoton emissions; determining probability of finding N backgroundphotons; and determining probability of having N photons due totransistor emission events.
 17. The method of claim 1 wherein theoperation of processing further comprises convolving the photon emissiondata with a normalized gate function.